Coverage Enhancement for Wireless Sensor Network Using Levy Flight Whale Optimization Algorithm

Abstract

WSNs is a collection of sensor nodes with the capacity of recognizing, physical changes from the  environment such as pressure, wind, air pollution, temperature, humidity, forest fire detection, vibration and  many others wirelessly among themselves. Coverage of a sensor node is one of the factors that affect  the strength and reliability of wireless sensor networks (WSNs) in the present technology, Coverage is the  most crucial factor in evaluating WSN quality since it represents how well a region is monitored, despite  having several real-world applications in a wide range of sectors, WSN deployment face a number of challenges related to the physical characteristics of the sensors and the expectation of a reliable network  system was increasing. Efforts have been made to make sure the field of interest is explicitly monitored,  nevertheless, the accurate placement of individual nodes is not auspicious in numerous cases which result in  coverage holes. Therefore, this research makes use of mobile sensors in improving the wireless sensor  nodes coverage, which can move iteratively to a better location with the use of Levy flight whale optimization algorithm (LWOA). the research depict that the proposed LWOA achieved full coverage with  time lesser than that of the MILP and also covered 147 cells whereas the MILP covered 142 cells as such,  LWOA out performs the MILP.